Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations64016
Missing cells364386
Missing cells (%)40.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory36.2 MiB
Average record size in memory593.7 B

Variable types

Text5
Categorical1
Numeric6
DateTime2

Alerts

jp_sales is highly overall correlated with total_salesHigh correlation
na_sales is highly overall correlated with other_sales and 2 other fieldsHigh correlation
other_sales is highly overall correlated with na_sales and 2 other fieldsHigh correlation
pal_sales is highly overall correlated with na_sales and 2 other fieldsHigh correlation
total_sales is highly overall correlated with jp_sales and 3 other fieldsHigh correlation
critic_score has 57338 (89.6%) missing values Missing
total_sales has 45094 (70.4%) missing values Missing
na_sales has 51379 (80.3%) missing values Missing
jp_sales has 57290 (89.5%) missing values Missing
pal_sales has 51192 (80.0%) missing values Missing
other_sales has 48888 (76.4%) missing values Missing
release_date has 7051 (11.0%) missing values Missing
last_update has 46137 (72.1%) missing values Missing
total_sales has 1352 (2.1%) zeros Zeros
pal_sales has 2245 (3.5%) zeros Zeros
other_sales has 5165 (8.1%) zeros Zeros

Reproduction

Analysis started2025-05-10 22:45:33.552260
Analysis finished2025-05-10 22:45:43.532668
Duration9.98 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

img
Text

Distinct56177
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size6.1 MiB
2025-05-10T22:45:43.907112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length142
Median length134
Mean length42.19995
Min length24

Characters and Unicode

Total characters2701472
Distinct characters46
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56146 ?
Unique (%)87.7%

Sample

1st row/games/boxart/full_6510540AmericaFrontccc.jpg
2nd row/games/boxart/full_5563178AmericaFrontccc.jpg
3rd row/games/boxart/827563ccc.jpg
4th row/games/boxart/full_9218923AmericaFrontccc.jpg
5th row/games/boxart/full_4990510AmericaFrontccc.jpg
ValueCountFrequency (%)
games/boxart/default.jpg 7810
 
12.2%
games/boxart/full_5005338americafrontccc.jpg 2
 
< 0.1%
games/boxart/full_342194americafrontccc.jpg 2
 
< 0.1%
games/boxart/full_5597924americafrontccc.jpg 2
 
< 0.1%
games/boxart/full_kaizou-chounin-shubibinman_5japanfront.jpg 2
 
< 0.1%
games/boxart/full_1834338americafrontccc.jpg 2
 
< 0.1%
games/boxart/full_faxanadu_6americafront.jpg 2
 
< 0.1%
games/boxart/full_8181689americafrontccc.jpg 2
 
< 0.1%
games/boxart/full_5972930japanfrontccc.jpg 2
 
< 0.1%
games/boxart/full_3233699americafrontccc.jpg 2
 
< 0.1%
Other values (56167) 56188
87.8%
2025-05-10T22:45:44.538902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 209321
 
7.7%
/ 192048
 
7.1%
c 177587
 
6.6%
r 158188
 
5.9%
g 133223
 
4.9%
t 132621
 
4.9%
o 127215
 
4.7%
e 125260
 
4.6%
l 111807
 
4.1%
m 103252
 
3.8%
Other values (36) 1230950
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1910889
70.7%
Decimal Number 343732
 
12.7%
Other Punctuation 256067
 
9.5%
Uppercase Letter 103965
 
3.8%
Connector Punctuation 58017
 
2.1%
Dash Punctuation 28802
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 209321
 
11.0%
c 177587
 
9.3%
r 158188
 
8.3%
g 133223
 
7.0%
t 132621
 
6.9%
o 127215
 
6.7%
e 125260
 
6.6%
l 111807
 
5.9%
m 103252
 
5.4%
p 79349
 
4.2%
Other values (16) 553066
28.9%
Decimal Number
ValueCountFrequency (%)
2 35605
10.4%
1 35394
10.3%
3 34963
10.2%
9 34903
10.2%
4 34884
10.1%
8 34743
10.1%
6 34583
10.1%
7 34545
10.0%
5 34471
10.0%
0 29641
8.6%
Uppercase Letter
ValueCountFrequency (%)
F 47886
46.1%
A 36907
35.5%
J 10980
 
10.6%
L 4096
 
3.9%
P 4096
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/ 192048
75.0%
. 64018
 
25.0%
: 1
 
< 0.1%
Connector Punctuation
ValueCountFrequency (%)
_ 58017
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28802
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2014854
74.6%
Common 686618
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 209321
 
10.4%
c 177587
 
8.8%
r 158188
 
7.9%
g 133223
 
6.6%
t 132621
 
6.6%
o 127215
 
6.3%
e 125260
 
6.2%
l 111807
 
5.5%
m 103252
 
5.1%
p 79349
 
3.9%
Other values (21) 657031
32.6%
Common
ValueCountFrequency (%)
/ 192048
28.0%
. 64018
 
9.3%
_ 58017
 
8.4%
2 35605
 
5.2%
1 35394
 
5.2%
3 34963
 
5.1%
9 34903
 
5.1%
4 34884
 
5.1%
8 34743
 
5.1%
6 34583
 
5.0%
Other values (5) 127460
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2701472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 209321
 
7.7%
/ 192048
 
7.1%
c 177587
 
6.6%
r 158188
 
5.9%
g 133223
 
4.9%
t 132621
 
4.9%
o 127215
 
4.7%
e 125260
 
4.6%
l 111807
 
4.1%
m 103252
 
3.8%
Other values (36) 1230950
45.6%

title
Text

Distinct39798
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Memory size4.9 MiB
2025-05-10T22:45:45.064822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length147
Median length100
Mean length22.062266
Min length1

Characters and Unicode

Total characters1412338
Distinct characters155
Distinct categories18 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28464 ?
Unique (%)44.5%

Sample

1st rowGrand Theft Auto V
2nd rowGrand Theft Auto V
3rd rowGrand Theft Auto: Vice City
4th rowGrand Theft Auto V
5th rowCall of Duty: Black Ops 3
ValueCountFrequency (%)
the 9848
 
4.2%
of 6174
 
2.7%
2 3855
 
1.7%
2962
 
1.3%
no 2670
 
1.1%
3 1536
 
0.7%
ii 1286
 
0.6%
world 1195
 
0.5%
game 990
 
0.4%
to 974
 
0.4%
Other values (23186) 200829
86.4%
2025-05-10T22:45:45.671788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168342
 
11.9%
e 116672
 
8.3%
a 94851
 
6.7%
o 85626
 
6.1%
i 76709
 
5.4%
r 74801
 
5.3%
n 72907
 
5.2%
t 61491
 
4.4%
s 55088
 
3.9%
l 46196
 
3.3%
Other values (145) 559655
39.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 950254
67.3%
Uppercase Letter 228098
 
16.2%
Space Separator 168342
 
11.9%
Other Punctuation 33390
 
2.4%
Decimal Number 25416
 
1.8%
Dash Punctuation 4670
 
0.3%
Open Punctuation 862
 
0.1%
Close Punctuation 862
 
0.1%
Math Symbol 294
 
< 0.1%
Final Punctuation 47
 
< 0.1%
Other values (8) 103
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 116672
12.3%
a 94851
10.0%
o 85626
 
9.0%
i 76709
 
8.1%
r 74801
 
7.9%
n 72907
 
7.7%
t 61491
 
6.5%
s 55088
 
5.8%
l 46196
 
4.9%
u 39590
 
4.2%
Other values (33) 226323
23.8%
Uppercase Letter
ValueCountFrequency (%)
S 24705
 
10.8%
T 18234
 
8.0%
C 14508
 
6.4%
A 13772
 
6.0%
M 13724
 
6.0%
D 13578
 
6.0%
P 11794
 
5.2%
B 11705
 
5.1%
R 11422
 
5.0%
F 9874
 
4.3%
Other values (18) 84782
37.2%
Other Letter
ValueCountFrequency (%)
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (14) 14
56.0%
Other Punctuation
ValueCountFrequency (%)
: 20778
62.2%
' 4021
 
12.0%
! 3013
 
9.0%
. 2909
 
8.7%
& 1182
 
3.5%
/ 488
 
1.5%
, 408
 
1.2%
? 212
 
0.6%
* 186
 
0.6%
; 64
 
0.2%
Other values (8) 129
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 7598
29.9%
0 5548
21.8%
1 3353
13.2%
3 2616
 
10.3%
4 1611
 
6.3%
9 1242
 
4.9%
5 1168
 
4.6%
6 846
 
3.3%
7 740
 
2.9%
8 694
 
2.7%
Other Symbol
ValueCountFrequency (%)
7
31.8%
® 6
27.3%
° 3
13.6%
2
 
9.1%
© 1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Math Symbol
ValueCountFrequency (%)
+ 210
71.4%
~ 78
 
26.5%
= 3
 
1.0%
1
 
0.3%
× 1
 
0.3%
< 1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
- 4575
98.0%
69
 
1.5%
26
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 842
97.7%
[ 20
 
2.3%
Close Punctuation
ValueCountFrequency (%)
) 842
97.7%
] 20
 
2.3%
Modifier Symbol
ValueCountFrequency (%)
´ 4
57.1%
^ 3
42.9%
Other Number
ValueCountFrequency (%)
² 2
66.7%
³ 1
33.3%
Format
ValueCountFrequency (%)
1
50.0%
 1
50.0%
Space Separator
ValueCountFrequency (%)
168342
100.0%
Final Punctuation
ValueCountFrequency (%)
47
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 25
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 13
100.0%
Initial Punctuation
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1178345
83.4%
Common 233962
 
16.6%
Hiragana 12
 
< 0.1%
Han 8
 
< 0.1%
Greek 7
 
< 0.1%
Katakana 4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 116672
 
9.9%
a 94851
 
8.0%
o 85626
 
7.3%
i 76709
 
6.5%
r 74801
 
6.3%
n 72907
 
6.2%
t 61491
 
5.2%
s 55088
 
4.7%
l 46196
 
3.9%
u 39590
 
3.4%
Other values (60) 454414
38.6%
Common
ValueCountFrequency (%)
168342
72.0%
: 20778
 
8.9%
2 7598
 
3.2%
0 5548
 
2.4%
- 4575
 
2.0%
' 4021
 
1.7%
1 3353
 
1.4%
! 3013
 
1.3%
. 2909
 
1.2%
3 2616
 
1.1%
Other values (51) 11209
 
4.8%
Hiragana
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Han
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Greek
ValueCountFrequency (%)
α 7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1411936
> 99.9%
None 240
 
< 0.1%
Punctuation 125
 
< 0.1%
Hiragana 12
 
< 0.1%
CJK 8
 
< 0.1%
Letterlike Symbols 7
 
< 0.1%
Misc Symbols 4
 
< 0.1%
Katakana 4
 
< 0.1%
Arrows 1
 
< 0.1%
Specials 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168342
 
11.9%
e 116672
 
8.3%
a 94851
 
6.7%
o 85626
 
6.1%
i 76709
 
5.4%
r 74801
 
5.3%
n 72907
 
5.2%
t 61491
 
4.4%
s 55088
 
3.9%
l 46196
 
3.3%
Other values (79) 559253
39.6%
None
ValueCountFrequency (%)
é 116
48.3%
26
 
10.8%
ö 13
 
5.4%
ú 12
 
5.0%
α 7
 
2.9%
® 6
 
2.5%
ä 6
 
2.5%
ü 5
 
2.1%
ë 5
 
2.1%
· 5
 
2.1%
Other values (22) 39
 
16.2%
Punctuation
ValueCountFrequency (%)
69
55.2%
47
37.6%
6
 
4.8%
2
 
1.6%
1
 
0.8%
Letterlike Symbols
ValueCountFrequency (%)
7
100.0%
Hiragana
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Misc Symbols
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Arrows
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Specials
ValueCountFrequency (%)
1
100.0%
Distinct81
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size3.6 MiB
2025-05-10T22:45:45.886859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.713103
Min length2

Characters and Unicode

Total characters173682
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowPS3
2nd rowPS4
3rd rowPS2
4th rowX360
5th rowPS4
ValueCountFrequency (%)
pc 12617
19.7%
ps2 3565
 
5.6%
ds 3288
 
5.1%
ps4 2878
 
4.5%
ps 2707
 
4.2%
ns 2337
 
3.7%
xbl 2120
 
3.3%
psn 2004
 
3.1%
xone 1963
 
3.1%
ps3 1905
 
3.0%
Other values (71) 28632
44.7%
2025-05-10T22:45:46.209074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 31659
18.2%
S 31273
18.0%
C 15487
 
8.9%
X 8191
 
4.7%
N 8088
 
4.7%
D 6524
 
3.8%
B 6463
 
3.7%
i 6401
 
3.7%
G 5696
 
3.3%
3 5143
 
3.0%
Other values (40) 48757
28.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 135797
78.2%
Decimal Number 19105
 
11.0%
Lowercase Letter 18780
 
10.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P 31659
23.3%
S 31273
23.0%
C 15487
11.4%
X 8191
 
6.0%
N 8088
 
6.0%
D 6524
 
4.8%
B 6463
 
4.8%
G 5696
 
4.2%
A 4785
 
3.5%
W 4245
 
3.1%
Other values (13) 13386
9.9%
Lowercase Letter
ValueCountFrequency (%)
i 6401
34.1%
n 3677
19.6%
e 2969
15.8%
l 2276
 
12.1%
d 1051
 
5.6%
r 516
 
2.7%
s 464
 
2.5%
x 459
 
2.4%
u 412
 
2.2%
t 134
 
0.7%
Other values (8) 421
 
2.2%
Decimal Number
ValueCountFrequency (%)
3 5143
26.9%
2 4146
21.7%
4 3305
17.3%
0 3001
15.7%
6 2666
14.0%
5 721
 
3.8%
8 60
 
0.3%
7 59
 
0.3%
1 4
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 154577
89.0%
Common 19105
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 31659
20.5%
S 31273
20.2%
C 15487
10.0%
X 8191
 
5.3%
N 8088
 
5.2%
D 6524
 
4.2%
B 6463
 
4.2%
i 6401
 
4.1%
G 5696
 
3.7%
A 4785
 
3.1%
Other values (31) 30010
19.4%
Common
ValueCountFrequency (%)
3 5143
26.9%
2 4146
21.7%
4 3305
17.3%
0 3001
15.7%
6 2666
14.0%
5 721
 
3.8%
8 60
 
0.3%
7 59
 
0.3%
1 4
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 173682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 31659
18.2%
S 31273
18.0%
C 15487
 
8.9%
X 8191
 
4.7%
N 8088
 
4.7%
D 6524
 
3.8%
B 6463
 
3.7%
i 6401
 
3.7%
G 5696
 
3.3%
3 5143
 
3.0%
Other values (40) 48757
28.1%

genre
Categorical

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.9 MiB
Misc
9304 
Action
8557 
Adventure
6260 
Role-Playing
5721 
Sports
5586 
Other values (15)
28588 

Length

Max length16
Median length10
Mean length7.4658523
Min length3

Characters and Unicode

Total characters477934
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAction
2nd rowAction
3rd rowAction
4th rowAction
5th rowShooter

Common Values

ValueCountFrequency (%)
Misc 9304
14.5%
Action 8557
13.4%
Adventure 6260
9.8%
Role-Playing 5721
8.9%
Sports 5586
8.7%
Shooter 5410
8.5%
Platform 4001
6.2%
Strategy 3685
 
5.8%
Puzzle 3521
 
5.5%
Racing 3425
 
5.4%
Other values (10) 8546
13.3%

Length

2025-05-10T22:45:46.335205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
misc 9304
14.4%
action 8557
13.3%
adventure 6260
9.7%
role-playing 5721
8.9%
sports 5586
8.7%
shooter 5410
8.4%
platform 4001
6.2%
strategy 3685
 
5.7%
puzzle 3521
 
5.5%
racing 3425
 
5.3%
Other values (12) 9072
14.1%

Most occurring characters

ValueCountFrequency (%)
t 46649
 
9.8%
i 40759
 
8.5%
o 40301
 
8.4%
e 35137
 
7.4%
n 33297
 
7.0%
r 27003
 
5.6%
c 23495
 
4.9%
l 23108
 
4.8%
a 20755
 
4.3%
A 18571
 
3.9%
Other values (26) 168859
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 397440
83.2%
Uppercase Letter 72370
 
15.1%
Dash Punctuation 7598
 
1.6%
Space Separator 526
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 46649
11.7%
i 40759
10.3%
o 40301
10.1%
e 35137
 
8.8%
n 33297
 
8.4%
r 27003
 
6.8%
c 23495
 
5.9%
l 23108
 
5.8%
a 20755
 
5.2%
g 17565
 
4.4%
Other values (12) 89371
22.5%
Uppercase Letter
ValueCountFrequency (%)
A 18571
25.7%
S 17859
24.7%
P 13394
18.5%
M 9831
13.6%
R 9146
12.6%
F 2367
 
3.3%
V 493
 
0.7%
N 493
 
0.7%
O 115
 
0.2%
E 35
 
< 0.1%
Other values (2) 66
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 7598
100.0%
Space Separator
ValueCountFrequency (%)
526
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 469810
98.3%
Common 8124
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 46649
 
9.9%
i 40759
 
8.7%
o 40301
 
8.6%
e 35137
 
7.5%
n 33297
 
7.1%
r 27003
 
5.7%
c 23495
 
5.0%
l 23108
 
4.9%
a 20755
 
4.4%
A 18571
 
4.0%
Other values (24) 160735
34.2%
Common
ValueCountFrequency (%)
- 7598
93.5%
526
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 477934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 46649
 
9.8%
i 40759
 
8.5%
o 40301
 
8.4%
e 35137
 
7.4%
n 33297
 
7.0%
r 27003
 
5.6%
c 23495
 
4.9%
l 23108
 
4.8%
a 20755
 
4.3%
A 18571
 
3.9%
Other values (26) 168859
35.3%
Distinct3383
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size4.2 MiB
2025-05-10T22:45:46.632216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length49
Median length40
Mean length11.121376
Min length2

Characters and Unicode

Total characters711946
Distinct characters86
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1227 ?
Unique (%)1.9%

Sample

1st rowRockstar Games
2nd rowRockstar Games
3rd rowRockstar Games
4th rowRockstar Games
5th rowActivision
ValueCountFrequency (%)
unknown 8845
 
8.7%
entertainment 5167
 
5.1%
games 4679
 
4.6%
interactive 3778
 
3.7%
sega 2213
 
2.2%
bandai 1868
 
1.8%
namco 1763
 
1.7%
sony 1735
 
1.7%
konami 1700
 
1.7%
arts 1672
 
1.6%
Other values (3519) 67927
67.0%
2025-05-10T22:45:47.367778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 72158
 
10.1%
e 57006
 
8.0%
t 54685
 
7.7%
o 52038
 
7.3%
a 49154
 
6.9%
i 46753
 
6.6%
r 37558
 
5.3%
37292
 
5.2%
s 28635
 
4.0%
m 24320
 
3.4%
Other values (76) 252347
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 553352
77.7%
Uppercase Letter 115358
 
16.2%
Space Separator 37332
 
5.2%
Decimal Number 3358
 
0.5%
Other Punctuation 2087
 
0.3%
Dash Punctuation 423
 
0.1%
Math Symbol 11
 
< 0.1%
Open Punctuation 9
 
< 0.1%
Close Punctuation 9
 
< 0.1%
Connector Punctuation 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 72158
13.0%
e 57006
10.3%
t 54685
9.9%
o 52038
9.4%
a 49154
8.9%
i 46753
8.4%
r 37558
 
6.8%
s 28635
 
5.2%
m 24320
 
4.4%
c 22995
 
4.2%
Other values (19) 108050
19.5%
Uppercase Letter
ValueCountFrequency (%)
S 14331
12.4%
U 11076
 
9.6%
E 11074
 
9.6%
A 9020
 
7.8%
I 7668
 
6.6%
G 7295
 
6.3%
C 6945
 
6.0%
N 5511
 
4.8%
M 5455
 
4.7%
T 5227
 
4.5%
Other values (17) 31756
27.5%
Decimal Number
ValueCountFrequency (%)
5 800
23.8%
3 800
23.8%
2 658
19.6%
0 371
11.0%
1 343
10.2%
7 164
 
4.9%
4 103
 
3.1%
9 73
 
2.2%
8 41
 
1.2%
6 5
 
0.1%
Other Punctuation
ValueCountFrequency (%)
. 1503
72.0%
, 229
 
11.0%
& 110
 
5.3%
! 106
 
5.1%
' 71
 
3.4%
/ 63
 
3.0%
* 2
 
0.1%
@ 2
 
0.1%
: 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
37292
99.9%
  40
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 8
88.9%
[ 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 8
88.9%
] 1
 
11.1%
Math Symbol
ValueCountFrequency (%)
+ 6
54.5%
~ 5
45.5%
Dash Punctuation
ValueCountFrequency (%)
- 423
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 668710
93.9%
Common 43236
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 72158
 
10.8%
e 57006
 
8.5%
t 54685
 
8.2%
o 52038
 
7.8%
a 49154
 
7.4%
i 46753
 
7.0%
r 37558
 
5.6%
s 28635
 
4.3%
m 24320
 
3.6%
c 22995
 
3.4%
Other values (46) 223408
33.4%
Common
ValueCountFrequency (%)
37292
86.3%
. 1503
 
3.5%
5 800
 
1.9%
3 800
 
1.9%
2 658
 
1.5%
- 423
 
1.0%
0 371
 
0.9%
1 343
 
0.8%
, 229
 
0.5%
7 164
 
0.4%
Other values (20) 653
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 711901
> 99.9%
None 45
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 72158
 
10.1%
e 57006
 
8.0%
t 54685
 
7.7%
o 52038
 
7.3%
a 49154
 
6.9%
i 46753
 
6.6%
r 37558
 
5.3%
37292
 
5.2%
s 28635
 
4.0%
m 24320
 
3.4%
Other values (71) 252302
35.4%
None
ValueCountFrequency (%)
  40
88.9%
é 2
 
4.4%
Ü 1
 
2.2%
ä 1
 
2.2%
ó 1
 
2.2%
Distinct8862
Distinct (%)13.8%
Missing17
Missing (%)< 0.1%
Memory size4.3 MiB
2025-05-10T22:45:47.668655image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length68
Median length52
Mean length12.73084
Min length2

Characters and Unicode

Total characters814761
Distinct characters94
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3933 ?
Unique (%)6.1%

Sample

1st rowRockstar North
2nd rowRockstar North
3rd rowRockstar North
4th rowRockstar North
5th rowTreyarch
ValueCountFrequency (%)
games 6130
 
5.2%
unknown 4447
 
3.8%
entertainment 3551
 
3.0%
studios 3516
 
3.0%
software 2861
 
2.4%
interactive 2128
 
1.8%
corporation 1675
 
1.4%
inc 1608
 
1.4%
studio 1432
 
1.2%
konami 1190
 
1.0%
Other values (7654) 89227
75.8%
2025-05-10T22:45:48.123332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 67378
 
8.3%
a 61367
 
7.5%
n 61084
 
7.5%
o 58996
 
7.2%
t 55262
 
6.8%
53630
 
6.6%
i 51892
 
6.4%
r 40751
 
5.0%
s 33703
 
4.1%
m 26784
 
3.3%
Other values (84) 303914
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 616269
75.6%
Uppercase Letter 134228
 
16.5%
Space Separator 53780
 
6.6%
Other Punctuation 6326
 
0.8%
Decimal Number 3082
 
0.4%
Dash Punctuation 952
 
0.1%
Open Punctuation 47
 
< 0.1%
Close Punctuation 47
 
< 0.1%
Math Symbol 15
 
< 0.1%
Connector Punctuation 10
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 67378
10.9%
a 61367
10.0%
n 61084
9.9%
o 58996
9.6%
t 55262
 
9.0%
i 51892
 
8.4%
r 40751
 
6.6%
s 33703
 
5.5%
m 26784
 
4.3%
l 20493
 
3.3%
Other values (23) 138559
22.5%
Uppercase Letter
ValueCountFrequency (%)
S 20242
15.1%
C 10665
 
7.9%
G 9736
 
7.3%
E 9280
 
6.9%
A 7898
 
5.9%
I 7584
 
5.7%
T 7408
 
5.5%
U 6143
 
4.6%
M 5761
 
4.3%
B 5735
 
4.3%
Other values (18) 43776
32.6%
Other Punctuation
ValueCountFrequency (%)
. 3984
63.0%
, 1039
 
16.4%
/ 496
 
7.8%
' 431
 
6.8%
& 262
 
4.1%
! 71
 
1.1%
: 30
 
0.5%
* 4
 
0.1%
@ 4
 
0.1%
? 4
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 597
19.4%
2 502
16.3%
3 426
13.8%
5 415
13.5%
0 258
8.4%
7 254
8.2%
4 251
8.1%
9 179
 
5.8%
8 101
 
3.3%
6 99
 
3.2%
Space Separator
ValueCountFrequency (%)
53630
99.7%
  150
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 46
97.9%
[ 1
 
2.1%
Close Punctuation
ValueCountFrequency (%)
) 46
97.9%
] 1
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 952
100.0%
Math Symbol
ValueCountFrequency (%)
+ 15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Other Number
ValueCountFrequency (%)
³ 2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 750497
92.1%
Common 64264
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 67378
 
9.0%
a 61367
 
8.2%
n 61084
 
8.1%
o 58996
 
7.9%
t 55262
 
7.4%
i 51892
 
6.9%
r 40751
 
5.4%
s 33703
 
4.5%
m 26784
 
3.6%
l 20493
 
2.7%
Other values (51) 272787
36.3%
Common
ValueCountFrequency (%)
53630
83.5%
. 3984
 
6.2%
, 1039
 
1.6%
- 952
 
1.5%
1 597
 
0.9%
2 502
 
0.8%
/ 496
 
0.8%
' 431
 
0.7%
3 426
 
0.7%
5 415
 
0.6%
Other values (23) 1792
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 814586
> 99.9%
None 173
 
< 0.1%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 67378
 
8.3%
a 61367
 
7.5%
n 61084
 
7.5%
o 58996
 
7.2%
t 55262
 
6.8%
53630
 
6.6%
i 51892
 
6.4%
r 40751
 
5.0%
s 33703
 
4.1%
m 26784
 
3.3%
Other values (72) 303739
37.3%
None
ValueCountFrequency (%)
  150
86.7%
ç 5
 
2.9%
Ü 3
 
1.7%
ø 3
 
1.7%
é 3
 
1.7%
à 2
 
1.2%
³ 2
 
1.2%
ä 2
 
1.2%
ý 1
 
0.6%
ë 1
 
0.6%
Punctuation
ValueCountFrequency (%)
2
100.0%

critic_score
Real number (ℝ)

Missing 

Distinct89
Distinct (%)1.3%
Missing57338
Missing (%)89.6%
Infinite0
Infinite (%)0.0%
Mean7.2204403
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2025-05-10T22:45:48.254571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q16.4
median7.5
Q38.3
95-th percentile9.1
Maximum10
Range9
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.4570656
Coefficient of variation (CV)0.20179734
Kurtosis0.828948
Mean7.2204403
Median Absolute Deviation (MAD)0.9
Skewness-0.91063686
Sum48218.1
Variance2.1230403
MonotonicityNot monotonic
2025-05-10T22:45:48.411346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 355
 
0.6%
7 332
 
0.5%
7.5 277
 
0.4%
8.5 214
 
0.3%
9 207
 
0.3%
8.3 203
 
0.3%
6 202
 
0.3%
7.9 196
 
0.3%
8.2 192
 
0.3%
8.1 190
 
0.3%
Other values (79) 4310
 
6.7%
(Missing) 57338
89.6%
ValueCountFrequency (%)
1 2
 
< 0.1%
1.2 1
 
< 0.1%
1.3 1
 
< 0.1%
1.4 1
 
< 0.1%
1.5 4
 
< 0.1%
1.7 2
 
< 0.1%
1.8 1
 
< 0.1%
1.9 2
 
< 0.1%
2 11
< 0.1%
2.1 2
 
< 0.1%
ValueCountFrequency (%)
10 16
 
< 0.1%
9.9 3
 
< 0.1%
9.8 3
 
< 0.1%
9.7 17
 
< 0.1%
9.6 26
 
< 0.1%
9.5 46
0.1%
9.4 41
0.1%
9.3 76
0.1%
9.2 82
0.1%
9.1 95
0.1%

total_sales
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct482
Distinct (%)2.5%
Missing45094
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean0.34911267
Minimum0
Maximum20.32
Zeros1352
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2025-05-10T22:45:48.550099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median0.12
Q30.34
95-th percentile1.37
Maximum20.32
Range20.32
Interquartile range (IQR)0.31

Descriptive statistics

Standard deviation0.8074622
Coefficient of variation (CV)2.3128986
Kurtosis125.55245
Mean0.34911267
Median Absolute Deviation (MAD)0.1
Skewness8.7753333
Sum6605.91
Variance0.6519952
MonotonicityDecreasing
2025-05-10T22:45:48.696304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 1366
 
2.1%
0 1352
 
2.1%
0.02 1228
 
1.9%
0.03 941
 
1.5%
0.04 768
 
1.2%
0.05 684
 
1.1%
0.06 631
 
1.0%
0.07 572
 
0.9%
0.08 514
 
0.8%
0.09 442
 
0.7%
Other values (472) 10424
 
16.3%
(Missing) 45094
70.4%
ValueCountFrequency (%)
0 1352
2.1%
0.01 1366
2.1%
0.02 1228
1.9%
0.03 941
1.5%
0.04 768
1.2%
0.05 684
1.1%
0.06 631
1.0%
0.07 572
0.9%
0.08 514
 
0.8%
0.09 442
 
0.7%
ValueCountFrequency (%)
20.32 1
< 0.1%
19.39 1
< 0.1%
16.15 1
< 0.1%
15.86 1
< 0.1%
15.09 1
< 0.1%
14.82 1
< 0.1%
14.74 1
< 0.1%
13.94 1
< 0.1%
13.86 1
< 0.1%
13.8 1
< 0.1%

na_sales
Real number (ℝ)

High correlation  Missing 

Distinct320
Distinct (%)2.5%
Missing51379
Missing (%)80.3%
Infinite0
Infinite (%)0.0%
Mean0.26474005
Minimum0
Maximum9.76
Zeros280
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2025-05-10T22:45:48.843557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.05
median0.12
Q30.28
95-th percentile0.99
Maximum9.76
Range9.76
Interquartile range (IQR)0.23

Descriptive statistics

Standard deviation0.4947866
Coefficient of variation (CV)1.8689526
Kurtosis78.62858
Mean0.26474005
Median Absolute Deviation (MAD)0.09
Skewness6.8983729
Sum3345.52
Variance0.24481378
MonotonicityNot monotonic
2025-05-10T22:45:48.975861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.04 651
 
1.0%
0.01 649
 
1.0%
0.02 640
 
1.0%
0.03 628
 
1.0%
0.05 617
 
1.0%
0.06 556
 
0.9%
0.07 525
 
0.8%
0.08 471
 
0.7%
0.09 445
 
0.7%
0.1 408
 
0.6%
Other values (310) 7047
 
11.0%
(Missing) 51379
80.3%
ValueCountFrequency (%)
0 280
0.4%
0.01 649
1.0%
0.02 640
1.0%
0.03 628
1.0%
0.04 651
1.0%
0.05 617
1.0%
0.06 556
0.9%
0.07 525
0.8%
0.08 471
0.7%
0.09 445
0.7%
ValueCountFrequency (%)
9.76 1
< 0.1%
9.07 1
< 0.1%
9.06 1
< 0.1%
8.54 1
< 0.1%
8.41 1
< 0.1%
8.27 1
< 0.1%
7.08 1
< 0.1%
6.99 1
< 0.1%
6.8 1
< 0.1%
6.76 1
< 0.1%

jp_sales
Real number (ℝ)

High correlation  Missing 

Distinct121
Distinct (%)1.8%
Missing57290
Missing (%)89.5%
Infinite0
Infinite (%)0.0%
Mean0.1022807
Minimum0
Maximum2.13
Zeros420
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2025-05-10T22:45:49.120160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.04
Q30.12
95-th percentile0.39
Maximum2.13
Range2.13
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.16881138
Coefficient of variation (CV)1.6504714
Kurtosis30.528417
Mean0.1022807
Median Absolute Deviation (MAD)0.03
Skewness4.4904062
Sum687.94
Variance0.028497281
MonotonicityNot monotonic
2025-05-10T22:45:49.258435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.01 1137
 
1.8%
0.02 845
 
1.3%
0.03 619
 
1.0%
0.04 452
 
0.7%
0 420
 
0.7%
0.05 329
 
0.5%
0.06 301
 
0.5%
0.07 248
 
0.4%
0.08 212
 
0.3%
0.09 168
 
0.3%
Other values (111) 1995
 
3.1%
(Missing) 57290
89.5%
ValueCountFrequency (%)
0 420
 
0.7%
0.01 1137
1.8%
0.02 845
1.3%
0.03 619
1.0%
0.04 452
 
0.7%
0.05 329
 
0.5%
0.06 301
 
0.5%
0.07 248
 
0.4%
0.08 212
 
0.3%
0.09 168
 
0.3%
ValueCountFrequency (%)
2.13 2
< 0.1%
2.05 2
< 0.1%
1.87 1
< 0.1%
1.82 1
< 0.1%
1.69 2
< 0.1%
1.5 1
< 0.1%
1.48 1
< 0.1%
1.45 1
< 0.1%
1.44 2
< 0.1%
1.43 1
< 0.1%

pal_sales
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct256
Distinct (%)2.0%
Missing51192
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean0.14947208
Minimum0
Maximum9.85
Zeros2245
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2025-05-10T22:45:49.408584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01
median0.04
Q30.14
95-th percentile0.59
Maximum9.85
Range9.85
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.39265263
Coefficient of variation (CV)2.6269295
Kurtosis147.20484
Mean0.14947208
Median Absolute Deviation (MAD)0.04
Skewness9.5869097
Sum1916.83
Variance0.15417608
MonotonicityNot monotonic
2025-05-10T22:45:49.552102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2245
 
3.5%
0.01 1635
 
2.6%
0.02 1290
 
2.0%
0.03 959
 
1.5%
0.04 717
 
1.1%
0.05 552
 
0.9%
0.06 422
 
0.7%
0.07 358
 
0.6%
0.08 297
 
0.5%
0.09 274
 
0.4%
Other values (246) 4075
 
6.4%
(Missing) 51192
80.0%
ValueCountFrequency (%)
0 2245
3.5%
0.01 1635
2.6%
0.02 1290
2.0%
0.03 959
1.5%
0.04 717
 
1.1%
0.05 552
 
0.9%
0.06 422
 
0.7%
0.07 358
 
0.6%
0.08 297
 
0.5%
0.09 274
 
0.4%
ValueCountFrequency (%)
9.85 1
< 0.1%
9.71 1
< 0.1%
8.64 1
< 0.1%
7.95 1
< 0.1%
6.87 1
< 0.1%
6.46 1
< 0.1%
6.21 2
< 0.1%
6.05 1
< 0.1%
5.88 1
< 0.1%
5.78 1
< 0.1%

other_sales
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct133
Distinct (%)0.9%
Missing48888
Missing (%)76.4%
Infinite0
Infinite (%)0.0%
Mean0.043040719
Minimum0
Maximum3.12
Zeros5165
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2025-05-10T22:45:49.682225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.01
Q30.03
95-th percentile0.18
Maximum3.12
Range3.12
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.1266435
Coefficient of variation (CV)2.9424113
Kurtosis144.48453
Mean0.043040719
Median Absolute Deviation (MAD)0.01
Skewness9.7945504
Sum651.12
Variance0.016038575
MonotonicityNot monotonic
2025-05-10T22:45:49.818226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5165
 
8.1%
0.01 3609
 
5.6%
0.02 1690
 
2.6%
0.03 939
 
1.5%
0.04 628
 
1.0%
0.05 475
 
0.7%
0.06 364
 
0.6%
0.07 327
 
0.5%
0.08 215
 
0.3%
0.09 182
 
0.3%
Other values (123) 1534
 
2.4%
(Missing) 48888
76.4%
ValueCountFrequency (%)
0 5165
8.1%
0.01 3609
5.6%
0.02 1690
 
2.6%
0.03 939
 
1.5%
0.04 628
 
1.0%
0.05 475
 
0.7%
0.06 364
 
0.6%
0.07 327
 
0.5%
0.08 215
 
0.3%
0.09 182
 
0.3%
ValueCountFrequency (%)
3.12 1
< 0.1%
3.02 1
< 0.1%
2.93 1
< 0.1%
2.46 1
< 0.1%
2.44 1
< 0.1%
2.28 1
< 0.1%
2.26 1
< 0.1%
2.12 1
< 0.1%
2.05 1
< 0.1%
1.82 1
< 0.1%

release_date
Date

Missing 

Distinct7922
Distinct (%)13.9%
Missing7051
Missing (%)11.0%
Memory size500.3 KiB
Minimum1971-12-03 00:00:00
Maximum2024-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-10T22:45:49.955665image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:50.117063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

last_update
Date

Missing 

Distinct1545
Distinct (%)8.6%
Missing46137
Missing (%)72.1%
Memory size500.3 KiB
Minimum2017-11-28 00:00:00
Maximum2024-01-28 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-05-10T22:45:50.257620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:50.404552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2025-05-10T22:45:41.102491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:37.722631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.349941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.037612image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.877155image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.490476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:41.381417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:37.834922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.463820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.130200image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.979454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.585966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:41.500829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:37.939394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.596212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.246080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.088293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.709652image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:41.602522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.032521image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.707924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.346604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.187989image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.808203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:41.720228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.133279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.816395image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.674924image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.288193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.904206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:41.822994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.234745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:38.927621image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:39.774575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:40.391257image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-10T22:45:41.002068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-05-10T22:45:50.516572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
critic_scoregenrejp_salesna_salesother_salespal_salestotal_sales
critic_score1.0000.0640.1330.3680.3090.3260.338
genre0.0641.0000.0700.0280.0220.0160.036
jp_sales0.1330.0701.0000.001-0.113-0.0000.546
na_sales0.3680.0280.0011.0000.7580.6520.926
other_sales0.3090.022-0.1130.7581.0000.7810.867
pal_sales0.3260.016-0.0000.6520.7811.0000.827
total_sales0.3380.0360.5460.9260.8670.8271.000

Missing values

2025-05-10T22:45:42.197073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-10T22:45:42.421394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-05-10T22:45:43.218573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

imgtitleconsolegenrepublisherdevelopercritic_scoretotal_salesna_salesjp_salespal_salesother_salesrelease_datelast_update
0/games/boxart/full_6510540AmericaFrontccc.jpgGrand Theft Auto VPS3ActionRockstar GamesRockstar North9.420.326.370.999.853.122013-09-17NaN
1/games/boxart/full_5563178AmericaFrontccc.jpgGrand Theft Auto VPS4ActionRockstar GamesRockstar North9.719.396.060.609.713.022014-11-182018-01-03
2/games/boxart/827563ccc.jpgGrand Theft Auto: Vice CityPS2ActionRockstar GamesRockstar North9.616.158.410.475.491.782002-10-28NaN
3/games/boxart/full_9218923AmericaFrontccc.jpgGrand Theft Auto VX360ActionRockstar GamesRockstar NorthNaN15.869.060.065.331.422013-09-17NaN
4/games/boxart/full_4990510AmericaFrontccc.jpgCall of Duty: Black Ops 3PS4ShooterActivisionTreyarch8.115.096.180.416.052.442015-11-062018-01-14
5/games/boxart/full_call-of-duty-modern-warfare-3_517AmericaFront.jpgCall of Duty: Modern Warfare 3X360ShooterActivisionInfinity Ward8.714.829.070.134.291.332011-11-08NaN
6/games/boxart/full_call-of-duty-black-ops_5AmericaFront.jpgCall of Duty: Black OpsX360ShooterActivisionTreyarch8.814.749.760.113.731.142010-11-09NaN
7/games/boxart/full_4653215AmericaFrontccc.jpgRed Dead Redemption 2PS4Action-AdventureRockstar GamesRockstar Games9.813.945.260.216.212.262018-10-262018-11-02
8/games/boxart/full_1977964AmericaFrontccc.jpgCall of Duty: Black Ops IIX360ShooterActivisionTreyarch8.413.868.270.074.321.202012-11-132018-04-07
9/games/boxart/full_4649679AmericaFrontccc.pngCall of Duty: Black Ops IIPS3ShooterActivisionTreyarch8.013.804.990.655.882.282012-11-132018-04-07
imgtitleconsolegenrepublisherdevelopercritic_scoretotal_salesna_salesjp_salespal_salesother_salesrelease_datelast_update
64006/games/boxart/default.jpgWithout WithinPCVisual NovelInvertMouseInvertMouseNaNNaNNaNNaNNaNNaN2015-01-222018-12-25
64007/games/boxart/default.jpgWithout Within 2PCVisual NovelInvertMouseInvertMouseNaNNaNNaNNaNNaNNaN2015-11-092018-12-25
64008/games/boxart/default.jpgWithout Within 3PCVisual NovelInvertMouseInvertMouseNaNNaNNaNNaNNaNNaN2018-05-032018-12-25
64009/games/boxart/full_2129671JapanFrontccc.jpgWorld End SyndromePSVVisual NovelArc System WorksArc System WorksNaNNaNNaNNaNNaNNaN2018-04-262019-04-03
64010/games/boxart/full_2294305JapanFrontccc.jpgWorld End SyndromePS4Visual NovelArc System WorksArc System WorksNaNNaNNaNNaNNaNNaN2018-04-262019-04-03
64011/games/boxart/full_2779838AmericaFrontccc.jpgXBlaze Lost: MemoriesPCVisual NovelAksys GamesArc System WorksNaNNaNNaNNaNNaNNaN2016-08-112019-01-28
64012/games/boxart/full_8031506AmericaFrontccc.jpgYoru, TomosuPS4Visual NovelNippon Ichi SoftwareNippon Ichi SoftwareNaNNaNNaNNaNNaNNaN2020-07-302020-05-09
64013/games/boxart/full_6553045AmericaFrontccc.jpgYoru, TomosuNSVisual NovelNippon Ichi SoftwareNippon Ichi SoftwareNaNNaNNaNNaNNaNNaN2020-07-302020-05-09
64014/games/boxart/full_6012940JapanFrontccc.pngYunohana SpRING! ~Mellow Times~NSVisual NovelIdea FactoryOtomateNaNNaNNaNNaNNaNNaN2019-02-282019-02-24
64015/games/boxart/default.jpgYurukill: The Calumniation GamesPS4Visual NovelUnknownG.rev Ltd.NaNNaNNaNNaNNaNNaNNaN2023-09-29